Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal Ilmu Dasar Journal of Energy, Material, and Instrumentation Technology
Syahputra, Tri Siswandi
Unknown Affiliation
Control & Systems Engineering Electrical & Electronics Engineering Energy Materials Science & Nanotechnology Mathematics Physics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
The Effect of Nonwoven Microfiber Substrate Polypropylene Thickness to Air Filtration Performance of Polyacrilonitrille Nanofiber Rajak, Abdul; Syahputra, Tri Siswandi; Munir, Muhammad Miftahul; Khairurrijal, K.
Jurnal ILMU DASAR Vol 20 No 2 (2019)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1512.963 KB) | DOI: 10.19184/jid.v20i2.9658

Abstract

Since a nanofiber medium on itself is soft and fragile and cannot be used alone as air filters. Coating nanofiber on a rigid substrate to form a composite that can be handled readily is necessary. Beside can improve the filtration efficiency, adding the substrate will also save the use of nanofibers mat itself. The aim of this study is to evaluate the effect of substrate thickness on the performance of nanofibers mat in aerosol filtration in order to find the optimum thickness of substrate that can increase the quality of nanofiber filter. The substrate used was a low cost microfiber non-woven fabric made from polypropylene (PP). The nanofibers mat was composed of electrospun polyacrylonitrile (PAN) with concentration of 9 wt.% which dissolved at N,N dimethylformamide (DMF). Five variations of PP different in thickness was used as substrate. From the SEM image, it was found that there is increasing fiber diameter of PAN after electrospun into PP substrate. From the porosity estimation of each nanofiber, it was found that the porosity decreased with increasing the substrate thickness. For test the performance of nanofiber filter, the particles of polystyrene latex (PSL) which generated by atomizer was used as the aerosol particle. In addition, to evaluate the performance filter in PM2.5 filtration, the experiment was carried out with generate the smoke from burning incense. Air filtration performance of all variations is obtained by comparison the results of measurement including: pressure drop, efficiency and quality factor. From the results, there is limitation on the substrates thickness based on the value of the quality factor obtained. Overall, PP nonwoven as the substrates gives the great contribution on the efficiency of PAN nanofiber. Keywords: substrate, polypropylene, thickness, nanofiber, air filtration.
Development of a Portable Low-Cost Multispectral Sensor Integrated with IoT and Machine Learning for Classifying Honey Types Muhammad, Riki; Isroni; wisesa, Tri Pujian; Syahputra, Tri Siswandi
Journal of Energy, Material, and Instrumentation Technology Vol 6 No 3 (2025): Journal of Energy, Material, and Instrumentation Technology
Publisher : Departement of Physics, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jemit.343

Abstract

Accurate honey type authentication is a significant challenge for small-scale producers, as conventional methods are often costly and impractical. This study aims to design and develop a low-cost honey classification prototype by integrating the AS7265X multispectral sensor with Internet of Things (IoT) technology and machine learning. Spectral data from 18 channels of various Indonesian honey types were acquired using the AS7265X sensor and analyzed exploratively using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). The data were then normalized and used to train Artificial Neural Network (ANN), Random Forest (RF), and Support Vector Machine (SVM) classification models. An ESP32-based IoT system was developed for real-time monitoring and cloud data storage. The results demonstrate that AS7265X spectral data effectively differentiate honey types, with the ANN model achieving 94.05% accuracy, supported by a responsive IoT system (1–2 seconds) for monitoring and centralized storage. This prototype shows potential as a practical, rapid, accurate, and efficient honey authentication solution for various stakeholders.
Co-Authors Isroni Khairurrijal Khairurrijal Muhammad Miftahul Munir Muhammad, Riki Rajak, Abdul wisesa, Tri Pujian